Centenarian controls increase variant effect sizes by an average twofold in an extreme case–extreme control analysis of Alzheimer’s disease
Open accessPublished version of a preprint
Abstract
Abstract The detection of genetic loci associated with Alzheimer’s disease (AD) requires large numbers of cases and controls because variant effect-sizes are mostly small. We hypothesized that variant effect-sizes should increase when individuals who represent the extreme ends of a disease spectrum are considered, as their genomes are assumed to be maximally enriched or depleted with disease-associated genetic variants. We used 1,073 extensively phenotyped AD cases with relatively young age at onset as extreme cases (66.3±7.9 years), 1,664 age-matched controls (66.0±6.5 years) and 255 cognitively healthy centenarians as extreme controls (101.4±1.3 years). We estimated the effect-size of 29 variants that were previously associated with AD in genome-wide association studies. Comparing extreme AD-cases with centenarian-controls increased the variant effect-size relative to published effect-sizes by on average 1.90-fold ( SE =0.29, p =9.0×10 −4 ). The effect-size increase was largest for the rare high-impact TREM2 (R74H) variant (6.5-fold), and significant for variants in/near ECHDC3 (4.6-fold), SLC24A4-RIN3 (4.5-fold), NME8 (3.8-fold), PLCG2 (3.3-fold), APOE-ε2 (2.2-fold) and APOE - ε4 (2.0-fold). Comparing extreme phenotypes enabled us to replicate the AD association for 10 variants ( p <0.05) in relatively small samples. The increase in effect-sizes depended mainly on using centenarians as extreme controls: the average variant effect-size was not increased in a comparison of extreme AD cases and age-matched controls (0.94-fold, p =6.8×10 −1 ), suggesting that on average the tested genetic variants did not explain the extremity of the AD-cases. Concluding, using centenarians as extreme controls in AD case-controls studies boosts the variant effect-size by on average two-fold, allowing the replication of disease-association in relatively small samples.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The initial genetic results for P522R and decreased AD risk were replicated by various independent cohorts.
“The initial genetic results were replicated by various independent cohorts (160, 161, 162).”
From The role of PLCγ2 in immunological disorders, cancer, and neurodegeneration (2021) · cites this paper as [161]
The Discussion says this study provides independent replication of previously reported AD-associated variants in a Dutch population. Table 2 reports an association between the PLCG2 variant and AD, consistent with decreased risk, but the paper describes one independent Dutch study—not replication by various independent cohorts. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089 · see citing works
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247 · see citing works
Principal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248 · see citing works
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336 · see citing works
Strittmatter, W. J., Saunders, A. M., Schmechel, D., Pericak-Vance, M., Enghild, J., Salvesen, G. S., & Roses, A. D. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.5.1977 · Cited by 4,268 · see citing works
Next-generation genotype imputation service and methods
Das, S., Forer, L., Schönherr, S., Sidore, C., Locke, A. E., Kwong, A., Vrieze, S. I., Chew, E. Y., Levy, S., McGue, M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3656 · Cited by 4,190 · see citing works
Association of apolipoprotein E allele ϵ4 with late‐onset familial and sporadic Alzheimer's disease
Saunders, A. M., Strittmatter, W. J., Schmechel, D., St. George-Hyslop, P. H., Pericak-Vance, M. A., Joo, S. H., Rosi, B. L., Gusella, J. F., Crapper-MacLachlan, D. R., Alberts, M. J., et al. (1993) · Neurology · doi:10.1212/wnl.43.8.1467 · Cited by 3,786 · see citing works
Harold, D., Abraham, R., Hollingworth, P., Sims, R., Gerrish, A., Hamshere, M. L., Pahwa, J. S., Moskvina, V., Dowzell, K., Williams, A., et al. (2009) · Nature Genetics · doi:10.1038/ng.440 · Cited by 3,326 · see citing works
<i>TREM2</i> Variants in Alzheimer's Disease
Guerreiro, R., Wojtas, A., Bras, J., Carrasquillo, M., Rogaeva, E., Majounie, E., Cruchaga, C., Sassi, C., Kauwe, J. S. K., Younkin, S., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1211851 · Cited by 3,020 · see citing works
A reference panel of 64,976 haplotypes for genotype imputation
the Haplotype Reference Consortium (2016) · Nature Genetics · doi:10.1038/ng.3643 · Cited by 2,836 · see citing works
Variant of <i>TREM2</i> Associated with the Risk of Alzheimer's Disease
Jonsson, T., Stefansson, H., Steinberg, S., Jonsdottir, I., Jonsson, P. V., Snaedal, J., Bjornsson, S., Huttenlocher, J., Levey, A. I., Lah, J. J., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1211103 · Cited by 2,558 · see citing works
Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer's disease
the European Alzheimer's Disease Initiative Investigators, Lambert, J.-C., Heath, S., Even, G., Campion, D., Sleegers, K., Hiltunen, M., Combarros, O., Zelenika, D., Bullido, M. J., et al. (2009) · Nature Genetics · doi:10.1038/ng.439 · Cited by 2,234 · see citing works
Ward, L. D., & Kellis, M. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr917 · Cited by 2,229 · see citing works
Initiative, T. A. D. N., Hollingworth, P., CHARGE consortium, EADI1 consortium, Harold, D., Sims, R., Gerrish, A., Lambert, J.-C., Carrasquillo, M. M., Abraham, R., et al. (2011) · Nature Genetics · doi:10.1038/ng.803 · Cited by 1,997 · see citing works
Protective effect of apolipoprotein E type 2 allele for late onset Alzheimer disease
Corder, E. H., Saunders, A. M., Risch, N. J., Strittmatter, W. J., Schmechel, D. E., Gaskell, P. C., Rimmler, J. B., Locke, P. A., Conneally, P. M., Schmader, K. E., et al. (1994) · Nature Genetics · doi:10.1038/ng0694-180 · Cited by 1,920 · see citing works
Naj, A. C., Jun, G., Beecham, G. W., Wang, L.-S., Vardarajan, B. N., Buros, J., Gallins, P. J., Buxbaum, J. D., Jarvik, G. P., Crane, P. K., et al. (2011) · Nature Genetics · doi:10.1038/ng.801 · Cited by 1,901 · see citing works
Role of Genes and Environments for Explaining Alzheimer Disease
Gatz, M., Reynolds, C. A., Fratiglioni, L., Johansson, B., Mortimer, J. A., Berg, S., Fiske, A., & Pedersen, N. L. (2006) · Archives of General Psychiatry · doi:10.1001/archpsyc.63.2.168 · Cited by 1,798 · see citing works
Data quality control in genetic case-control association studies
Anderson, C. A., Pettersson, F. H., Clarke, G. M., Cardon, L. R., Morris, A. P., & Zondervan, K. T. (2010) · Nature Protocols · doi:10.1038/nprot.2010.116 · Cited by 1,318 · see citing works
Genome-wide Analysis of Genetic Loci Associated With Alzheimer Disease
Seshadri, S. (2010) · JAMA · doi:10.1001/jama.2010.574 · Cited by 1,219 · see citing works
New approaches to population stratification in genome-wide association studies
Price, A. L., Zaitlen, N., Reich, D., & Patterson, N. J. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2813 · Cited by 1,181 · see citing works
ARUK Consortium, Sims, R., GERAD/PERADES, C., van der Lee, S. J., Naj, A. C., Bellenguez, C., Badarinarayan, N., Jakobsdottir, J., Kunkle, B. W., Boland, A., et al. (2017) · Nature Genetics · doi:10.1038/ng.3916 · Cited by 1,126 · see citing works
Rare-Variant Association Analysis: Study Designs and Statistical Tests
Lee, S., Abecasis, G. R., Boehnke, M., & Lin, X. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.06.009 · Cited by 1,042 · see citing works
2012 Alzheimer's disease facts and figures Alzheimer's Association ∗
Thies, W. H., & Bleiler, L. (2012) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2012.02.001 · Cited by 984 · see citing works
The genetic landscape of Alzheimer disease: clinical implications and perspectives
Van Cauwenberghe, C., Van Broeckhoven, C., & Sleegers, K. (2016) · Genetics in Medicine · doi:10.1038/gim.2015.117 · Cited by 863 · see citing works
A General Approach for Haplotype Phasing across the Full Spectrum of Relatedness
O'Connell, J., Gurdasani, D., Delaneau, O., Pirastu, N., Ulivi, S., Cocca, M., Traglia, M., Huang, J., Huffman, J. E., Rudan, I., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004234 · Cited by 593 · see citing works
GWAS on family history of Alzheimer’s disease
Marioni, R. E., Harris, S. E., Zhang, Q., McRae, A. F., Hagenaars, S. P., Hill, W. D., Davies, G., Ritchie, C. W., Gale, C. R., Starr, J. M., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0150-6 · Cited by 564 · see citing works
Sample Size and Statistical Power Calculation in Genetic Association Studies
Hong, E. P., & Park, J. W. (2012) · Genomics & Informatics · doi:10.5808/gi.2012.10.2.117 · Cited by 541 · see citing works
Dementia incidence continues to increase with age in the oldest old: The 90+ study
Corrada, M. M., Brookmeyer, R., Paganini‐Hill, A., Berlau, D., & Kawas, C. H. (2010) · Annals of Neurology · doi:10.1002/ana.21915 · Cited by 523 · see citing works
Genetic influence on human lifespan and longevity
Hjelmborg, J., Iachine, I. A., Skytthe, A., Vaupel, J. W., McGue, M. K., Koskenvuo, M. J., Kaprio, J. A., Pedersen, N. L., & Christensen, K. (2006) · Human Genetics · doi:10.1007/s00439-006-0144-y · Cited by 498 · see citing works
Cohort Profile: The Longitudinal Aging Study Amsterdam
Huisman, M. A., Poppelaars, J. L., van der Horst, M., Beekman, A. T. F., Brug, J., van Tilburg, T. G., & Deeg, D. J. H. (2011) · International Journal of Epidemiology · doi:10.1093/ije/dyq219 · Cited by 467 · see citing works
Self-citationVarma, A. R., Snowden, J. S., Lloyd, J. J., Talbot, P. R., Mann, D. M. A., & Neary, D. (1999) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.66.2.184 · Cited by 400 · see citing works
Optimizing Patient Care and Research: The Amsterdam Dementia Cohort
van der Flier, W. M., Pijnenburg, Y. A. L., Prins, N. D., Lemstra, A. W., Bouwman, F. H., Teunissen, C. E., van Berckel, B. N. M., Stam, C. J., Barkhof, F., Visser, P. J., et al. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-132306 · Cited by 390 · see citing works
Self-citationGenetics of healthy aging and longevity
Brooks-Wilson, A. R. (2013) · Human Genetics · doi:10.1007/s00439-013-1342-z · Cited by 380 · see citing works
Amsterdam Dementia Cohort: Performing Research to Optimize Care
van der Flier, W. M., & Scheltens, P. (2018) · Journal of Alzheimer s Disease · doi:10.3233/jad-170850 · Cited by 379 · see citing works
Self-citationLoss-of-function variants in ABCA7 confer risk of Alzheimer's disease
DemGene, Steinberg, S., Stefansson, H., Jonsson, T., Johannsdottir, H., Ingason, A., Helgason, H., Sulem, P., Magnusson, O. T., Gudjonsson, S. A., et al. (2015) · Nature Genetics · doi:10.1038/ng.3246 · Cited by 324 · see citing works
A novel Alzheimer disease locus located near the gene encoding tau protein
Jun, G., Ibrahim-Verbaas, C. A., Vronskaya, M., Lambert, J.-C., Chung, J., Naj, A. C., Kunkle, B. W., Wang, L.-S., Bis, J. C., Bellenguez, C., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2015.23 · Cited by 297 · see citing works
Why Match? Investigating Matched Case-Control Study Designs with Causal Effect Estimation
Rose, S., & van der Laan, M. J. (2009) · The International Journal of Biostatistics · doi:10.2202/1557-4679.1127 · Cited by 293 · see citing works
Blacker, D., Albert, M., Bassett, S. S., Go, R. C. P., Harrell, L., & Folstein, M. (1994) · Archives of Neurology · doi:10.1001/archneur.1994.00540240042014 · Cited by 293 · see citing works
GWAS of Longevity in CHARGE Consortium Confirms APOE and FOXO3 Candidacy
Broer, L., Buchman, A. S., Deelen, J., Evans, D. S., Faul, J. D., Lunetta, K. L., Sebastiani, P., Smith, J. A., Smith, A. V., Tanaka, T., et al. (2014) · The Journals of Gerontology Series A · doi:10.1093/gerona/glu166 · Cited by 279 · see citing works
The Longitudinal Aging Study Amsterdam: cohort update 2016 and major findings
Hoogendijk, E. O., Deeg, D. J. H., Poppelaars, J. L., van der Horst, M. H. L., Groenou, M. I. B. V., Comijs, H. C., Pasman, H. R. W., van Schoor, N. M., Suanet, B., Thomése, F., et al. (2016) · European Journal of Epidemiology · doi:10.1007/s10654-016-0192-0 · Cited by 227 · see citing works
Self-citationJoshi, P. K., Pirastu, N., Kentistou, K. A., Fischer, K., Hofer, E., Schraut, K. E., Clark, D. W., Nutile, T., Barnes, C. L. K., Timmers, P. R. H. J., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00934-5 · Cited by 161 · see citing works
Li, D., Lewinger, J. P., Gauderman, W. J., Murcray, C. E., & Conti, D. V. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20628 · Cited by 140 · see citing works
Recommendations for CSF AD biomarkers in the diagnostic evaluation of dementia
Simonsen, A. H., Herukka, S.-K., Andreasen, N., Baldeiras, I., Bjerke, M., Blennow, K., Engelborghs, S., Frisoni, G. B., Gabryelewicz, T., Galluzzi, S., et al. (2017) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.09.008 · Cited by 138 · see citing works
Detecting Rare Variant Effects Using Extreme Phenotype Sampling in Sequencing Association Studies
Barnett, I., Lee, S., & Lin, X. (2012) · Genetic Epidemiology · doi:10.1002/gepi.21699 · Cited by 136 · see citing works
Polygenic Overlap Between C-Reactive Protein, Plasma Lipids, and Alzheimer Disease
Desikan, R. S., Schork, A. J., Wang, Y., Thompson, W. K., Dehghan, A., Ridker, P. M., Chasman, D. I., McEvoy, L. K., Holland, D., Chen, C.-H., et al. (2015) · Circulation · doi:10.1161/circulationaha.115.015489 · Cited by 135 · see citing works
Four Genome-Wide Association Studies Identify New Extreme Longevity Variants
Paola Sebastiani, B., Gurinovich, A., Bae, H. T., Andersen, S. L., Malovini, A. L., Atzmon, G., Villa, F., Kraja, A. T., Ben‐Avraham, D., Barzilai, N., et al. (2017) · The Journals of Gerontology Series A · doi:10.1093/gerona/glx027 · Cited by 113 · see citing works
The 100-plus Study of cognitively healthy centenarians: rationale, design and cohort description
Holstege, H., Beker, N., Dijkstra, T., Pieterse, K., Wemmenhove, E., Schouten, K., Thiessens, L., Horsten, D., Rechtuijt, S., Sikkes, S., et al. (2018) · bioRxiv · doi:10.1007/s10654-018-0451-3 · Cited by 86 · see citing works
Self-citationGaragnani, P., Giuliani, C., Pirazzini, C., Olivieri, F., Bacalini, M. G., Ostan, R., Mari, D., Passarino, G., Monti, D., Bonfigli, A. R., et al. (2013) · Aging · doi:10.18632/aging.100562 · Cited by 66 · see citing works
Phenotypic extremes in rare variant study designs
Peloso, G. M., Rader, D. J., Gabriel, S., Kathiresan, S., Daly, M. J., & Neale, B. M. (2016) · European Journal of Human Genetics · doi:10.1038/ejhg.2015.197 · Cited by 58 · see citing works
Genetic landscape of APOE in human longevity revealed by high-throughput sequencing
Ryu, S., Atzmon, G., Barzilai, N., Raghavachari, N., & Suh, Y. (2016) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2016.02.010 · Cited by 45 · see citing works
Genetic Analysis of 16 NMR‐Lipoprotein Fractions in Humans, the GOLDN Study
Kraja, A. T., Borecki, I. B., Tsai, M. Y., Ordovás, J. M., Hopkins, P. N., Lai, C., Wood, A. C., Straka, R. J., Hixson, J. E., Province, M. A., et al. (2012) · Lipids · doi:10.1007/s11745-012-3740-8 · Cited by 42 · see citing works
Identification of rare variants in Alzheimer’s disease
Lord, J., Lu, A. J., & Cruchaga, C. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00369 · Cited by 33 · see citing works
Genetic meta-analysis identifies 9 novel loci and functional pathways for Alzheimer’s disease riskPreprint
Jansen, I. E., Savage, J. E., Watanabe, K., Bryois, J., Williams, D. M., Steinberg, S., Sealock, J., Karlsson, I., Hägg, S., Athanasiu, L., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/258533 · Cited by 33 · see citing works
Self-citation14GENETIC META-ANALYSIS IDENTIFIES 9 NOVEL LOCI AND FUNCTIONAL PATHWAYS FOR ALZHEIMER'S DISEASE RISK
Danielle Posthuma, B., Jansen, I. E., Savage, J. E., Watanabe, K., Bryois, J., Williams, D. M., van der Flier, W. M., Dobson, R., Davis, L. K., Stefánsson, H., et al. (2019) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2018.08.021 · Cited by 6 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Interpretation of risk loci from genome-wide association studies of Alzheimer's disease
Andrews, S. J., Fulton-Howard, B., & Goate, A. (2020) · The Lancet Neurology · doi:10.1016/s1474-4422(19)30435-1 · Cited by 314 · see citing works
Alzheimer’s Disease: An Updated Overview of Its Genetics
Andrade-Guerrero, J., Santiago-Balmaseda, A., Jeronimo-Aguilar, P., Vargas-Rodríguez, I., Cadena-Suárez, A. R., Sánchez-Garibay, C., Pozo-Molina, G., Méndez-Catalá, C. F., Cardenas-Aguayo, M.-D.-C., Diaz-Cintra, S., et al. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24043754 · Cited by 336 · see citing works
Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores
Leonenko, G., Baker, E. A., Stevenson‐Hoare, J. O., Sierksma, A. S. R., Fiers, M. W. E. J., Williams, J. H., Strooper, B. D., & Escott‐Price, V. (2021) · Nature Communications · doi:10.1038/s41467-021-24082-z · Cited by 226 · see citing works
Tijms, B. M., Vromen, E. M., Mjaavatten, O., Holstege, H. H., Reus, L. M., van der Lee, S. J., Wesenhagen, K. E. J., Lorenzini, L., Vermunt, L., Venkatraghavan, V., et al. (2024) · Nature Aging · doi:10.1038/s43587-023-00550-7 · Cited by 222 · see citing works
Self-citationDESGESCO (Dementia Genetics Spanish Consortium), E. (. D. E. D. B., van der Lee, S. J., biobank), E. (. D. E. D., IFGC (International FTD-Genomics Consortium), I. (. I. P. D. G. C., IPDGC (The International Parkinson Disease Genomics Consortium), Dementia), R.-F. (. A. M. F. I. F.-T., (NBB), N. B. B., The GIFT (Genetic Investigation in Frontotemporal Dementia and Alzheimer’s Disease) Study Group, Conway, O. J., Jansen, I., et al. (2019) · Acta Neuropathologica · doi:10.1007/s00401-019-02026-8 · Cited by 120 · see citing works
Self-citationThe Longitudinal Aging Study Amsterdam: cohort update 2019 and additional data collections
Hoogendijk, E. O., Deeg, D. J. H., de Breij, S., Klokgieters, S. S., Kok, A. A. L., Stringa, N., Timmermans, E. J., van Schoor, N. M., van Zutphen, E. M., van der Horst, M. H. L., et al. (2019) · European Journal of Epidemiology · doi:10.1007/s10654-019-00541-2 · Cited by 128 · see citing works
Self-citationThe role of PLCγ2 in immunological disorders, cancer, and neurodegeneration
Jackson, J. T., Mulazzani, E., Nutt, S. L., & Masters, S. L. (2021) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2021.100905 · Cited by 113 · see citing works
Western, D., Timsina, J., Wang, L., Wang, C., Yang, C., Phillips, B., Wang, Y., Liu, M., Ali, M., Beric, A., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01972-8 · Cited by 111 · see citing works
Alzheimer Disease Prediction using Machine Learning Algorithms
Neelaveni, J., & Devasena, M. S. G. (2020) · International Conference on Advanced Computing and Communication Systems (ICACCS) · doi:10.1109/icaccs48705.2020.9074248 · Cited by 110 · see citing works
Phospholipase C families: Common themes and versatility in physiology and pathology
Katan, M., & Cockcroft, S. (2020) · Progress in Lipid Research · doi:10.1016/j.plipres.2020.101065 · Cited by 89 · see citing works
Upregulation of RIN3 induces endosomal dysfunction in Alzheimer’s disease
Shen, R., Zhao, X.-B., He, L., Ding, Y., Xu, W., Lin, S.-Z., Fang, S., Yang, W., Sung, K., Spencer, B., et al. (2020) · Translational Neurodegeneration · doi:10.1186/s40035-020-00206-1 · Cited by 69 · see citing works
Tesi, N., van der Lee, S. J., Hulsman, M., Jansen, I. E., Stringa, N., van Schoor, N. M., Scheltens, P., van der Flier, W. M., Huisman, M., Reinders, M. J. T., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-01018-7 · Cited by 67 · see citing works
Self-citationLongitudinal Maintenance of Cognitive Health in Centenarians in the 100-plus Study
Beker, N., Sikkes, S. A. M., Hulsman, M., Tesi, N., van der Lee, S. J., Scheltens, P., & Holstege, H. H. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.0094 · Cited by 61 · see citing works
Self-citationCognitively healthy centenarians are genetically protected against Alzheimer's disease
Tesi, N., van der Lee, S., Hulsman, M., van Schoor, N. M., Huisman, M., Pijnenburg, Y., van der Flier, W. M., Reinders, M., & Holstege, H. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.13810 · Cited by 52 · see citing works
Self-citationZhang, M., Ganz, A. B., Rohde, S., Rozemuller, A. J. M., Bank, N. B., Reinders, M. J. T., Scheltens, P., Hulsman, M., Hoozemans, J. J. M., & Holstege, H. (2023) · Alzheimer's & Dementia · doi:10.1002/alz.12899 · Cited by 43 · see citing works
Self-citationPolygenic Risk Score of Longevity Predicts Longer Survival Across an Age Continuum
Tesi, N., van der Lee, S. J., Hulsman, M., Jansen, I. E., Stringa, N., van Schoor, N. M., Scheltens, P., van der Flier, W. M., Huisman, M. A., Reinders, M. J. T., et al. (2020) · The Journals of Gerontology Series A · doi:10.1093/gerona/glaa289 · Cited by 37 · see citing works
Self-citationThe correlation between neuropathology levels and cognitive performance in centenarians
Zhang, M., Ganz, A. B., Rohde, S. K., Lorenz, L. M. C., Rozemüller, A. J. M., van Vliet, K., Graat, M., Sikkes, S. A. M., Reinders, M. J. T., Scheltens, P., et al. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13087 · Cited by 33 · see citing works
Self-citationGenetic resilience to Alzheimer's disease in <i>APOE</i> ε4 homozygotes: A systematic review
Huq, A. J., Fransquet, P., Laws, S. M., Ryan, J., Sebra, R., Masters, C. L., Winship, I. M., James, P. A., & Lacaze, P. (2019) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2019.05.011 · Cited by 35 · see citing works
Centenarians as Models of Resistance and Resilience to Alzheimer’s Disease and Related Dementias
Andersen, S. L. (2020) · Advances in Geriatric Medicine and Research · doi:10.20900/agmr20200018 · Cited by 31 · see citing works
Bhattacharyya, R., Teves, C. A. F., Long, A., Hofert, M., & Tanzi, R. E. (2022) · Scientific Reports · doi:10.1038/s41598-022-07372-4 · Cited by 27 · see citing works
Controlling the Impact of Helicobacter pylori-Related Hyperhomocysteinemia on Neurodegeneration
Kountouras, J., Doulberis, M., Papaefthymiou, A., Pοlyzos, S. A., Zavos, C., Kazakos, E. I., Arapoglou, S., Kyrailidi, F., Mouratidou, M. C., Boziki, M. K., et al. (2023) · Medicina · doi:10.3390/medicina59030504 · Cited by 28 · see citing works
Alzheimer’s Disease Genetics: Review of Novel Loci Associated with Disease
Tábuas-Pereira, M., Santana, I., Guerreiro, R., & Bras, J. (2020) · Current Genetic Medicine Reports · doi:10.1007/s40142-020-00182-y · Cited by 28 · see citing works
Fulton‐Howard, B., Goate, A., Adelson, R. P., Koppel, J. L., Gordon, M. L., Barzilai, N., Atzmon, G., Davies, P., & Freudenberg‐Hua, Y. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2020.09.014 · Cited by 25 · see citing works
Genetics Contributes to Concomitant Pathology and Clinical Presentation in Dementia with Lewy Bodies
van der Lee, S. J., van Steenoven, I., Beek, M. H. C. T. V., Tesi, N., Jansen, I. E., van Schoor, N. M., Reinders, M. J. T., Huisman, M. A., Scheltens, P., Teunissen, C. E., et al. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-210365 · Cited by 25 · see citing works
Self-citationRisk of dementia in <i>APOE</i> ε4 carriers is mitigated by a polygenic risk score
Ebenau, J. L., van der Lee, S. J., Hulsman, M., Tesi, N., Jansen, I. E., Verberk, I. M. W., van Leeuwenstijn, M., Teunissen, C. E., Barkhof, F., Prins, N. D., et al. (2021) · Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring · doi:10.1002/dad2.12229 · Cited by 19 · see citing works
Self-citationLinthorst, J., Meert, W., Hestand, M. S., Korlach, J., Vermeesch, J. R., Reinders, M. J. T., & Holstege, H. H. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-01060-5 · Cited by 25 · see citing works
Self-citationThe genetics of neurodegenerative diseases is the genetics of age-related damage clearance failure
Hardy, J., & Escott‐Price, V. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-02911-7 · Cited by 23 · see citing works
Regulation of K+-Dependent Na+/Ca2+-Exchangers (NCKX)
Al-Khannaq, M., & Lytton, J. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms24010598 · Cited by 22 · see citing works
TREM2 risk variants and associated endophenotypes in alzheimer’s disease
Dijkstra, J. I. R., Vermunt, L., Venkatraghavan, V., Ozhegov, G., Coomans, E. M., Ossenkoppele, R., van de Giessen, E., Hulsman, M., de Geus, C. M., van der Flier, W. M., et al. (2025) · Alzheimer's Research & Therapy · doi:10.1186/s13195-025-01700-2 · Cited by 18 · see citing works
Self-citationReus, L. M., Jansen, I. E., Mol, M. O., van Ruissen, F., van Rooij, J., van Schoor, N. M., Tesi, N., Reinders, M. J. T., Huisman, M. A., Holstege, H. H., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01577-3 · Cited by 18 · see citing works
Self-citationAlzheimer’s disease basics: we all should know
Das, S. K. (2025) · Neurological Research · doi:10.1080/01616412.2025.2529560 · Cited by 19 · see citing works
Huq, A. J., Fulton‐Howard, B., Riaz, M., Laws, S., Sebra, R., Ryan, J., Alzheimer's Disease Genetics Consortium, Renton, A. E., Goate, A. M., Masters, C. L., et al. (2021) · Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring · doi:10.1002/dad2.12226 · Cited by 17 · see citing works
Pitfalls of predicting age‐related traits by polygenic risk scores
Escott‐Price, V., & Schmidt, K. M. (2023) · Annals of Human Genetics · doi:10.1111/ahg.12520 · Cited by 16 · see citing works
Single nucleotide variations in ZBTB46 are associated with post-thrombolytic parenchymal haematoma
Carrera, C., Cárcel‐Márquez, J., Cullell, N., Torres‐Aguila, N. P., Muiño, E., Castillo, J., Sobrino, T., Campos, F., Castro, E. R., Llucià‐Carol, L., et al. (2021) · Brain · doi:10.1093/brain/awab090 · Cited by 15 · see citing works
Carriers of the p.P522R variant in PLCγ2 have a slightly more responsive immune system
Diks, A. M., Teodosio, C., de Mooij, B., Groenland, R. J., Naber, B. A. E., de Laat, I. F., Vloemans, S. A., Rohde, S., de Jonge, M. I., Lorenz, L., et al. (2023) · Molecular Neurodegeneration · doi:10.1186/s13024-023-00604-9 · Cited by 14 · see citing works
Self-citationRas and Rab Interactor 3: From Cellular Mechanisms to Human Diseases
Shen, R., Murphy, C. J., Xu, X., Hu, M., Ding, J., & Wu, C. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.824961 · Cited by 14 · see citing works
The Effect of Alzheimer’s Disease-Associated Genetic Variants on Longevity
Tesi, N., Hulsman, M., van der Lee, S. J., Jansen, I. E., Stringa, N., van Schoor, N. M., Scheltens, P., van der Flier, W. M., Huisman, M. A., Reinders, M. J. T., et al. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.748781 · Cited by 13 · see citing works
Self-citationEstablishing Best Practices for Clinical GWAS: Tackling Imputation and Data Quality Challenges
Casaburi, G., McCullough, R. M., & D’Argenio, V. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26136397 · Cited by 12 · see citing works
Gutman, D., Lidzbarsky, G. A., Milman, S., Gao, T., Sin‐Chan, P., Gonzaga-Jauregui, C. G., Deelen, J., Shuldiner, A. R., Barzilai, N., & Atzmon, G. (2020) · Aging Cell · doi:10.1111/acel.13216 · Cited by 12 · see citing works
Cálculo do custo da cesta básica de Vitória da Conquista – BA, no contexto da pandemia do SARS-CoV-2
Alves, D. R., Júnior, G. S., & Oliveira, J. V. S. (2022) · Cadernos de Ciências Sociais Aplicadas · doi:10.22481/ccsa.v19i33.10437 · Cited by 11 · see citing works
Osipowicz, M., Wilczyński, B., Machnicka, M. A., & Initiative, A. D. N. (2021) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqab069 · Cited by 11 · see citing works
The Role of RIN3 Gene in Alzheimer’s Disease Pathogenesis: a Comprehensive Review
Meshref, M. M., Ghaith, H. S., Hammad, M. A., Shalaby, M. M. M., Ayasra, F., Monib, F. A., Attia, M. S., Ebada, M. A., Elsayed, H., Shalash, A., et al. (2023) · Molecular Neurobiology · doi:10.1007/s12035-023-03802-0 · Cited by 11 · see citing works
Protective Effects of Familial Longevity Decrease With Age and Become Negligible for Centenarians
Gavrilova, N. S., & Gavrilov, L. A. (2021) · The Journals of Gerontology Series A · doi:10.1093/gerona/glab380 · Cited by 11 · see citing works
Tijms, B. M., Vromen, E. M., Mjaavatten, O., Holstege, H., Reus, L. M., van der Lee, S., Wesenhagen, K. E., Lorenzini, L., Vermunt, L., Venkatraghavan, V., et al. (2023) · doi:10.1101/2023.05.10.23289793 · Cited by 10 · see citing works
Self-citationShin, Y.-C., Plummer-Medeiros, A. M., Mungenast, A., Choi, H.-W., TenDyke, K., Zhu, X., Shepard, J., Sanders, K., Zhuang, N., Hu, L., et al. (2024) · Science Advances · doi:10.1126/sciadv.adn6037 · Cited by 7 · see citing works
Tesi, N., van der Lee, S. J., Hulsman, M., van Schoor, N. M., Huisman, M. A., Pijnenburg, Y. A. L., van der Flier, W. M., Reinders, M. J. T., & Holstege, H. H. (2023) · medRxiv · doi:10.1101/2023.05.16.23290049 · Cited by 7 · see citing works
Self-citationAn Effective and Efficient Alzheimer Disease Prediction System Using Machine Learning Model
Chowdary, B. V., Muppidi, S., Sruthi, B., Madhuri, K. S., & Sumanth, L. (2021) · International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · doi:10.1109/i-smac52330.2021.9641022 · Cited by 6 · see citing works
Improving Alzheimer’s Disease Detection with Transfer Learning
Dar, S. A., Rather, A. A., Araibi, M. I. A., Elbatal, I., Almetwally, E. M., Gemeay, A. M., Shukla, S., Danish, F., & Dar, Q. F. (2025) · International Journal of Statistics in Medical Research · doi:10.6000/1929-6029.2025.14.39 · Cited by 6 · see citing works
Reus, L. M., Boltz, T. A., Francia, M., Bot, M. H. M., Ramesh, N., Koromina, M., Pijnenburg, Y. A. L., den Braber, A., van der Flier, W. M., Visser, P. J., et al. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-02934-0 · Cited by 5 · see citing works
da Silva, S. P., Castro, C. C. M., Rabelo, L. N., Engelberth, R. C. G. J., Fernández‐Calvo, B., & Fiuza, F. P. (2023) · GeroScience · doi:10.1007/s11357-023-00982-4 · Cited by 5 · see citing works
Connecting dementia risk loci to the CSF proteome identifies pathophysiological leads for dementia
Reus, L. M., Jansen, I. E., Tijms, B. M., Visser, P. J., Tesi, N., van der Lee, S. J., Vermunt, L., Peeters, C. F. W., Groot, L. A. D., Hok‐A‐Hin, Y. S., et al. (2024) · Brain · doi:10.1093/brain/awae090 · Cited by 5 · see citing works
Self-citationZhang, M., Ganz, A. B., Rohde, S. K., Rozemüller, A. J. M., Bank, N. B., Reinders, M. J. T., Scheltens, P., Hulsman, M., Hoozemans, J. J. M., & Holstege, H. H. (2022) · medRxiv · doi:10.1101/2022.08.28.22279304 · Cited by 3 · see citing works
Self-citationDiagnosis of Alzheimer’s Disease using Machine Learning Algorithms
Rao, C. D., Charan, G. H., Mounika, G., Sri, K. K., Reddy, P. N. K., & Krishna, S. L. R. (2022) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2022.44978 · Cited by 2 · see citing works
Role of Machine Learning Algorithms on Alzheimer Disease Prediction
Kumar, V. K., Devasena, M. S. G., Gopu, G., & Sivakumaran, N. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-19-2500-9_57 · Cited by 1 · see citing works
Ruíz Moleón, V., Fotouhi, M., Alende, C., Ayoubi, R., Bedford, L. M., Southern, K., Richardson, T. I., Laflamme, C., NeuroSGC/YCharOS/EDDU collaborative group, & ABIF consortium (2024) · F1000Research · doi:10.12688/f1000research.146156.1 · Cited by 1 · see citing works
Early Predicting Alzheimer's Disease Using Multiple Machine Learning Techniques
Burle, R., & Dewangan, L. (2023) · International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI) · doi:10.1109/icaiihi57871.2023.10489834 · Cited by 1 · see citing works
Do genetic factors contribute to sex-specific differences in resilience to amyloid pathology?
Groot, C., Holstege, H. H., & Ossenkoppele, R. (2022) · Brain · doi:10.1093/brain/awac216 · Cited by 1 · see citing works
Self-citationRojas‐Martínez, A., Colistro, V., Cruz, R., Ruiz, C., Quintela, I., Carracedo, Á., Luna‐Pérez, P., Garcia-Gonzalez, I. S., Murillo, C. M., Ortı́z-López, R., et al. (2020) · doi:10.21203/rs.3.rs-36642/v1
Alzheimer Forecast Analysis u sing Machine Learning
Patil, P., & Kadu, S. (2022) · International Journal of Engineering and Advanced Technology · doi:10.35940/ijeat.d3461.0411422
Parkinson\'s Disease Prediction using Machine Learning Methods and Large Amounts of Data
Ammannamma, T., & Vandana, D. (2023) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2023.54218
TREM2 Risk Variants with Alzheimer’s Disease Differ in Rate of Cognitive DeclinePreprint
Dijkstra, J. I. R., Vermunt, L., Venkatraghavan, V., Ozhegov, G., Coomans, E. M., Ossenkoppele, R., van de Giessen, E., Hulsman, M., de Geus, C. M., van der Flier, W. M., et al. (2024) · Research Square · doi:10.21203/rs.3.rs-5310076/v1
Self-citationUnraveling Alzheimer's disease heterogeneity:
Vromen, E. M. (2024) · doi:10.5463/thesis.937
Sirvent, D. Á., Tesi, N., Hulsman, M., Salazar, A., van Schoor, N. M., Huisman, M. A., Pijnenburg, Y. A. L., van der Flier, W. M., Strijbis, E. M. M., Uitdehaag, B. M. J., et al. (2025) · medRxiv · doi:10.1101/2025.03.30.25324899
Self-citationSridhar, K. S., Gupta, V., Raj, D. J. R., & Reddy, M. P. (2026) · IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS) · doi:10.1109/sceecs68810.2026.11430140
CSF proteomic quantitative trait loci mapping reveals genetic insights into Alzheimer’s disease
Reus, L. M., Jiang, C., Vilor‐Tejedor, N., Boltz, T. A., Yigit, A., Gobom, J., Vos, S. J. B., Blennow, K., Zetterberg, H., Martinez-Lage, P., et al. (2026) · Molecular Neurodegeneration Advances · doi:10.1186/s44477-026-00048-7
Self-citation
- Authors
- Tesi, N., van der Lee, S. J., Hulsman, M., Jansen, I. E., Stringa, N., van Schoor, N., Meijers-Heijboer, H., Huisman, M., Scheltens, P., Reinders, M. J. T., van der Flier, W. M., & Holstege, H.
- Affiliations
- Amsterdam UMC Location University of Amsterdam (NL)
- Amsterdam Neuroscience (NL)
- Amsterdam Public Health (NL)
- Delft University of Technology (NL)
- Corresponding author
- Holstege, Henne
- ORCID
- Venue
- European Journal of Human Genetics
- Published
- 2018-09-26
- Volume
- 27
- Issue
- 2
- Pages
- 244-253
- ISSN
- 1018-4813 (ISSN-L)
- 1476-5438
- PMC
- PMC6336855
- OpenAlex
- W2949491829
- Cited by
- 65
- References
- 54
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 8 · 2023: 11 · 2022: 10 · 2021: 11 · 2020: 13 · 2019: 2 · 2018: 1
- FWCI
- 4.64
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- European Journal of Human Genetics (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion, cc-by)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
- VU Research Portal (publishedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Research Repository (Delft University of Technology) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- ZonMw (733051061)
- Stichting Dioraphte (VSM 14 04 1402)
- Alzheimer Nederland (WE09.2014–03)
- Amsterdam Neuroscience
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- Alzheimer's disease, centenarians, replication of genetic associations, APOE ε4, APOE ε2, PLCγ2, age of onset, genetic loci
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Female, Humans, Male, Middle Aged, Sample Size, Patient Selection, Polymorphism, Single Nucleotide, Control Groups, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review